Development of <scp>model output statistics</scp> based on <scp>the least absolute shrinkage and selection operator</scp> regression for forecasting next‐day maximum temperature in South Korea-Reference-Cited by-同舟云学术

Development of model output statistics based on the least absolute shrinkage and selection operator regression for forecasting next‐day maximum temperature in South Korea

Published:2022-04 Issue:745 Volume:148 Page:1929-1944
ISSN:0035-9009
Container-title:Quarterly Journal of the Royal Meteorological Society
language:en
Short-container-title:Quart J Royal Meteoro Soc

Author:

Yoon Donghyuck¹^ORCID,Kim Kyoungmin¹,Cha Dong‐Hyun¹^ORCID,Lee Myong‐In¹,Im Jungho¹,Cho Dongjin¹^ORCID,Min Ki‐Hong²

Affiliation:

1. Department of Urban and Environmental Engineering Ulsan National Institute of Science and Technology Ulsan South Korea

2. Department of Astronomy and Atmospheric Sciences Kyungpook National University Daegu South Korea

Funder

Korea Meteorological Administration

Publisher

Wiley

Subject

Atmospheric Science

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/qj.4286

Reference39 articles.

2. The quiet revolution of numerical weather prediction

3. On the efficient computation of the nonlinear full-information maximum-likelihood estimator

4. A Model Output Deep Learning Method for Grid Temperature Forecasts in Tianjin Area

5. Strengths and Weaknesses of MOS, Running-Mean Bias Removal, and Kalman Filter Techniques for Improving Model Forecasts over the Western United States

Cited by 4 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Risks of heat waves in South Korea using structural equation modeling and entropy weighting;Stochastic Environmental Research and Risk Assessment;2024-04-17

2. A new statistical downscaling approach for short‐term forecasting of summer air temperatures through a fusion of deep learning and spatial interpolation;Quarterly Journal of the Royal Meteorological Society;2024-01-18

3. Detection of Soluble Solids Content (SSC) in Pears Using Near-Infrared Spectroscopy Combined with LASSO–GWF–PLS Model;Agriculture;2023-07-27

4. An extensive investigation on leveraging machine learning techniques for high-precision predictive modeling of CO ₂ emission;Energy Sources, Part A: Recovery, Utilization, and Environmental Effects;2023-07-09